Present day fixed income securities generally require ratings in order to be sold to investors. There are many reasons for this. Ratings act as a relative value and relative safety measure for all rated fixed income instruments. These ratings are used by investors to limit risk in mutual funds, and across their individual asset purchase decisions. Regulators use these ratings to limit risks at banks, investment banks and insurance companies globally. Ratings tools rate corporate, sovereign and structured securities of every kind. Rated structured securities include asset backed securities (ABS), asset backed commercial paper (ABCP), collateralized debt obligations (CDOs), collateralized synthetic obligations (CSOs), collateralized loan obligations (CLOs), residential mortgage backed securities (RMBS), commercial mortgage backed securities (CMBS) etc. Furthermore, ratings agencies use the ratings of these securities in order to then rate corporations which hold large quantities of securities themselves. In particular, they use these ratings to then help rate insurance companies, banks, monoline insurance companies, credit derivative product companies, etc.
In recent history, the ratings for these entities, while crucially important to the financial system, have failed to accurately detect the risk in these securities. As such, it has been desirable to design a new measure of risk which would better determine the risk of these securities with limited user intervention, for example automatically, by a computer. In particular, the Bank for International Settlements (BIS) Committee on the Global Financial system (CGFS) has called for a review of the existing ratings framework and has called for the design of an additional risk measure which would enhance current measures, in order to detect automatically the risks which rating agencies themselves appear to have missed during the financial crisis of 2007 and 2008.
U.S. Pat. No. 7,571,138 describes software which aggregates and integrates credit exposure and credit data across accounting, trading and operational systems within an organization and generates views of available credit in light of the exposure and credit limits. A comprehensive model of exposure to all counterparties, across all of their divisions and subsidiaries, is assembled, enabling the creation of a hierarchical view of each counterparty that models its real-world parent-child relationships.
United States Patent Application Publication No. 2008/0021804 describes a method and system for determining investor participation driven stock purchase indices. Raw customer trading data is received from an accounting system. The raw customer trading data is then aggregated to generate daily transaction total counts for all stocks (that is, total shares bought and sold, total market value, etc.) as well as daily transaction total counts for each individual stock. The aggregated data is processed to produce moving averages, stock purchase indices, and stock rankings. The stock purchase indices are based on a diffusion index technique of segregating buyers from sellers, and with these relative counts, measures the breadth of investor purchasing participation.
U.S. Pat. No. 7,558,751 describes a system that creates stock indices based on the “buy, sell and hold” research recommendations of research firms, tracks the performance of those indices, and allows clients to search for top performing indices according to a variety of search parameters and filters through a proprietary text navigation searching mechanism.
United States Patent Application Publication No. 2006/0015430 describes a method for creating indices of forecasts of performance regarding financial markets, in which a number of performances for each element of a number of markets and/or financial tools are considered as unknown variables; the described method comprises the following steps: defining an objective function as the sum of the squares of the differences of the homologous elements of the correlation matrix calculated on the variables and of the correlation matrix supplied as forecast, and minimizing said objective function using a non-linear programming algorithm for identification of global optima so as to obtain said indices of forecasts of performance regarding financial markets.
It is an object of the invention to provide an improved measure of risk of financial instruments. It is a further object of the invention to provide an index which represents an improved measure of risk of financial instruments.